Ontology & Research
The Knowledge Layer Beneath Every Agent
Before ISWIZ AI deploys a single agent, we build a formal ontology of your business — typed objects, semantic relationships, versioned properties, and inference rules. This knowledge layer is what separates AI that reasons from AI that guesses.
What Is an Ontology
A Formal Model of Your Business
An ontology is not a database schema and not a prompt template. It is a structured, machine-readable representation of the concepts, entities, and relationships that define your domain — clients, matters, procedures, instruments, regulations, workflows. When an agent queries your ontology, it retrieves semantically grounded facts, not keyword matches. The difference is the difference between a system that knows your business and one that approximates it.
Object Layer
Every entity in your business — client, matter, property, patient, instrument, regulation — is typed, versioned, and stored as a first-class object with defined properties and lifecycle states.
Relationship Graph
Objects are connected by typed, directional relationships: a client retains a matter, a matter involves a counterparty, a counterparty is governed by a jurisdiction. Agents traverse this graph to answer multi-hop questions without hallucinating intermediate steps.
Inference & Rules Engine
Domain rules — regulatory constraints, workflow preconditions, compliance thresholds — are encoded as first-order logic expressions evaluated against the graph. Agents invoke the rules engine before acting, ensuring every output is compliant by construction.
Audit & Provenance Log
Every agent action is logged against the ontology state at the time of execution — which objects were read, which rules were evaluated, which output was produced. The audit trail is queryable, exportable, and admissible.
Reasoning & Integration Layer
How Agents Act on the Ontology
The ontology defines what your business knows. The reasoning and integration layer defines how agents act on it — routing tasks to the right model, accessing data through a guarded tool layer, and logging every action for review.
01
Model Routing
Task Dispatch
Tasks are dispatched to the model best suited for them — on-premise inference for sensitive or latency-critical work, frontier cloud models when deeper reasoning is required. You control what stays local and what is permitted to route outbound.
02
Guarded Tool Layer
Data Access Control
Agents never query source systems directly. Every data access goes through a structured, read-only-by-default tool layer — validated queries, scoped to approved views, with numeric results computed exactly rather than predicted, eliminating hallucinated figures.
03
Audit & Provenance
Full Logging
Every tool call is logged — who made it, what was requested, when it ran, and what it returned. Any agent action can be reviewed and traced back to its source data, making the system auditable by the professionals responsible for the outcome.
Research Focus
Where We Are Pushing the Field
Ontology-Grounded RAG
Standard retrieval-augmented generation retrieves by semantic similarity. Our research extends RAG with ontology-constrained retrieval — documents are retrieved only when their entities and relationships match the query's ontological context, reducing irrelevant chunks and hallucinated citations.
Multi-Step Task Coordination
We are developing persistent task graph architectures that allow agents to maintain state across sessions, resume interrupted workflows, and coordinate work operating on different time horizons — from real-time document analysis to long-running background jobs.
Compliance-by-Construction
Rather than auditing AI outputs for compliance after the fact, we are building inference pipelines where regulatory constraints are encoded as hard preconditions evaluated before any output is generated. The agent cannot produce a non-compliant result — it is structurally prevented.
Contact
Start with an Ontology Workshop
Every ISWIZ AI engagement begins with a structured ontology workshop — a half-day session where we map your business objects, relationships, and processes before writing a single line of code.
Address
613 NW Loop 410 San Antonio, TX 78216